In this podcast, we spoke with Dr. George Wang, Vice President of Discovery and Preclinical Services at WuXi Biologics about the importance of identifying potential manufacturing, stability, and scalability challenges early to mitigate risks, reduce costs, and streamline drug development timelines. By evaluating factors such as solubility, stability, and manufacturability during initial candidate screening, companies can avoid costly setbacks later in the process. Advanced tools like high-throughput assays, computational modeling, and AI-based predictions are now essential for these evaluations.
What Is Developability?
Dr. Wang began by defining developability as the assessment of whether a drug candidate possesses the necessary attributes to be scaled up for production during Chemistry, Manufacturing, and Controls (CMC) development and, ultimately, for clinical trials and commercialization. He explained, “It’s about identifying potential red flags early on—issues like aggregation, degradation, or manufacturing inefficiencies—that could derail a candidate further down the line.”
Why Focus on Developability During Discovery?
Traditionally, discovery efforts have focused on identifying antibodies with the highest efficacy and safety profiles. However, the increasing complexity of biologics, including bispecific antibodies and antibody-drug conjugates, has shifted industry focus. Dr. Wang emphasized the costly consequences of overlooking developability in the discovery phase. “Imagine investing millions into a molecule, only to discover insurmountable stability or manufacturability issues during development,” he said. “Performing these assessments early is like an insurance policy, mitigating risks and saving time and resources.”
The Economic Case for Early Developability Assessments
Dr. Wang highlighted the economic rationale for incorporating developability assessments during the initial discovery phase. “The cost of discovery is less than 1% of the total development cost. Spending a bit more upfront can save millions in reengineering or restarting development,” he noted. He also pointed out that superior developability attributes can provide a competitive edge, enabling faster clinical trial entry or product approval.
Key Challenges and Industry Solutions
Despite its benefits, the integration of developability assessments in discovery labs faces challenges. Labs often lack the tools, materials, and expertise required for systematic evaluations. “Developability attributes must be assessed using a robust combination of computational methods, analytical tools, and high-throughput assays, which many labs are not equipped to handle,” Dr. Wang explained.
Companies like WuXi Biologics have stepped in to bridge this gap. “Our Discovery unit collaborates closely with our CMC team to identify and address developability issues early on,” said Dr. Wang. WuXi’s “WuXiDEEP™,” platform has become a cornerstone of their success, helping fix more than 50 problematic molecules and guiding hundreds of projects through the development pipeline.
A Stepwise Approach to Developability
Dr. Wang outlined a stepwise approach to developability assessments, starting with high-throughput evaluations during the initial screening of hundreds of candidates. “We use computational analysis to identify red flags such as post-translational modification hotspots or aggregation risks,” he explained. Promising candidates then undergo more detailed assessments, requiring larger material quantities and lower-throughput methods.
Even when issues arise, solutions like protein engineering can salvage candidates with strong biological functions. “It’s not about discarding problem molecules outright but addressing and optimizing their developability profiles,” Dr. Wang emphasized.
The Role of AI in Developability Assessments
Artificial intelligence (AI) is playing an increasingly significant role in drug discovery, and Dr.